NCSTN Antibody

What is Nicastrin (NCSTN) and why is it important for research?

Nicastrin is a type I transmembrane glycoprotein that serves as an essential component of the gamma-secretase complex. The gamma-secretase complex is a protease that catalyzes the intramembrane cleavage of integral membrane proteins, including Notch receptors and amyloid precursor proteins (APP) . Nicastrin is not catalytically active itself, but rather functions as a stabilizing cofactor required for gamma-secretase complex assembly .

Nicastrin has significant research importance due to its involvement in:

• Notch signaling pathway regulation

• Amyloid-beta peptide generation relevant to Alzheimer's disease pathology

• Cancer progression, particularly in hepatocellular carcinoma

• Wnt signaling cascades and regulation of downstream processes

Mutations in the NCSTN gene have also been associated with familial acne inversa, expanding its relevance to dermatological research .

What are the key applications for NCSTN antibodies in research?

NCSTN antibodies have multiple validated applications in research settings:

NCSTN antibodies have been successfully employed to study the role of nicastrin in cancer progression, particularly in hepatocellular carcinoma where NCSTN overexpression regulates cancer stem cell properties and induces epithelial-mesenchymal transition via Notch1 cleavage .

How do I select the appropriate NCSTN antibody for my experiment?

Selecting the optimal NCSTN antibody requires consideration of several factors:

Species reactivity: Many commercially available NCSTN antibodies react with human, mouse, and rat samples, but cross-reactivity should be verified before use . For example, the Sigma-Aldrich polyclonal antibody (#N1660) has been validated for human samples and also reacts with mouse protein despite a minor sequence mismatch in the immunogen sequence .

Antibody type: Both monoclonal (e.g., BioLegend 9C3 clone) and polyclonal (e.g., Sigma-Aldrich #N1660) NCSTN antibodies are commercially available . Monoclonals offer higher specificity for particular epitopes, while polyclonals may provide stronger signals by recognizing multiple epitopes.

Target region: Consider whether you need an antibody targeting:

• C-terminal region (e.g., Sigma-Aldrich #N1660, amino acids 693-709)

• N-terminal region (e.g., BiCell Scientific antibody, using a 15-aa synthetic peptide)

Application compatibility: Verify that the antibody has been validated for your specific application (WB, IHC, IF, etc.) with published validation data .

What methods exist for validating NCSTN antibodies?

Robust validation of NCSTN antibodies is critical for experimental reliability. The following approaches represent best practices:

• Knockout/knockdown controls: The gold standard for antibody validation is testing against knockout or knockdown samples. For example, researchers validated the Sigma-Aldrich #N1660 antibody using HEK293 wildtype cells alongside HEK293 cells with CRISPR/Cas9-mediated NCSTN knockout .

• Glycosylation analysis: Treating lysates with peptide-N-glycosidase F (PNGase F) to remove N-linked glycans confirms the identity of NCSTN bands, as demonstrated by the reduction of the ~110 kDa glycosylated form to less than 75 kDa .

• Multiple detection methods: Validate antibody specificity through multiple techniques (e.g., WB, IHC, IF) to ensure consistent target recognition across applications .

• Citation verification: Checking published literature with the antibody catalog number or Research Resource Identifier (RRID) can provide evidence of successful antibody use in peer-reviewed research .

• Peptide competition assays: Using the immunogen peptide to block antibody binding can demonstrate specificity for the target epitope .

Why does NCSTN appear at different molecular weights on Western blots?

The apparent molecular weight discrepancy of NCSTN on Western blots is primarily attributed to post-translational modifications, particularly glycosylation:

• Theoretical molecular weight: The calculated molecular weight of NCSTN is approximately 78.4 kDa based on amino acid sequence .

• Observed molecular weight (glycosylated): The mature glycosylated form typically appears at approximately 110 kDa on SDS-PAGE .

• Deglycosylated form: Treatment with PNGase F reduces the apparent molecular weight to less than 75 kDa .

This glycosylation is biologically significant as the heavily glycosylated ectodomain of nicastrin forms a horseshoe-like clamp on the extracellular portion of the gamma-secretase complex . The glycosylation pattern may vary between tissue types and experimental conditions, potentially affecting antibody recognition.

How can I optimize immunodetection of NCSTN in different sample types?

Optimizing NCSTN detection requires adjustments based on the sample type and experimental goals:

For Western blotting:

• Use appropriate lysis buffers that effectively solubilize membrane proteins

• Include protease inhibitors to prevent degradation

• Optimize primary antibody concentration (typically 0.1-2 μg/mL)

• Include positive controls (e.g., HEK293 cells) and negative controls (e.g., NCSTN knockout cells)

• For detecting both glycosylated and deglycosylated forms, consider PNGase F treatment of a portion of your sample

For immunohistochemistry/immunofluorescence:

• Optimize fixation methods (paraformaldehyde is commonly used)

• Consider antigen retrieval methods for formalin-fixed tissues

• Titrate antibody concentration (typically 1-5 μg/mL for IHC, 20 μg/mL for IF)

• Include appropriate blocking steps to reduce background

• Use species-specific secondary antibodies conjugated to appropriate detection systems (HRP for IHC, fluorophores for IF)

How does NCSTN contribute to disease pathology and what research models are available?

NCSTN's involvement in disease pathology extends across multiple conditions, with several established research models:

Alzheimer's disease: As part of the gamma-secretase complex, NCSTN contributes to amyloid-beta peptide generation . Research models include:

• HEK293 cells expressing wildtype or mutant amyloid precursor protein

• Transgenic mouse models with altered NCSTN expression

• CRISPR/Cas9-engineered NCSTN knockout cells

Cancer progression: NCSTN promotes hepatocellular carcinoma cell growth and metastasis through β-catenin activation in a Notch1/AKT dependent manner . Models include:

• HCC cell lines with NCSTN overexpression or silencing

• Xenograft tumor models to study in vivo effects of NCSTN alteration

Dermatological conditions: NCSTN mutations are associated with familial acne inversa , with research utilizing:

• Patient-derived cells with NCSTN mutations

• CRISPR-engineered cell lines mimicking patient mutations

What computational and experimental approaches can improve antibody design and specificity?

Advanced approaches to antibody design and specificity assessment combine computational modeling with experimental validation:

Computational approaches:

• Homology modeling using tools like PIGS server or AbPredict algorithm to build 3D models of antibody variable fragments

• Molecular dynamics simulations to refine 3D structures of antibody-antigen complexes

• Automated docking and screening against human glycome database to assess potential cross-reactivity

• Sequence analysis to predict epitope-paratope interactions

Combined computational-experimental methods:

• Quantitative glycan microarray screening to determine binding kinetics (KD values)

• Site-directed mutagenesis to identify key residues in antibody combining sites

• Saturation transfer difference NMR (STD-NMR) to define glycan-antigen contact surfaces

• High-throughput sequencing and computational analysis of phage display experiments to identify different binding modes

This integrated approach has successfully produced antibodies with customized specificity profiles, either with specific high affinity for particular target ligands or with cross-specificity for multiple target ligands .

How should NCSTN antibodies be properly documented in research publications?

Proper documentation of antibodies in publications is essential for research reproducibility. The Antibody Registry has established standards for antibody citation:

Required information:

• Vendor name and location

• Catalog number

• Clone name (for monoclonals)

• Research Resource Identifier (RRID)

Example citation format:
"Anti-nicastrin antibody (Sigma-Aldrich #N1660, St. Louis, MO; RRID:AB_477259) was used at 1:1000 dilution for Western blotting."

The Antibody Registry provides persistent identifiers (RRIDs) for antibodies that can be cited in publications. This practice has improved antibody identification in scientific literature, with uniquely identifiable antibody citations increasing from 12% in 1997 to 31% in 2020 .

What experimental controls are essential when working with NCSTN antibodies?

Rigorous experimental design requires appropriate controls to ensure valid interpretation of results:

Positive controls:

• Cell lines known to express NCSTN (e.g., HEK293, IMR-32)

• Tissue samples with confirmed NCSTN expression

• Recombinant NCSTN protein (when available)

Negative controls:

• NCSTN knockout or knockdown samples (e.g., CRISPR/Cas9-engineered NCSTN knockout HEK293 cells)

• Isotype control antibodies for immunoprecipitation or immunostaining

• Secondary antibody-only controls to assess non-specific binding

Technical controls:

• PNGase F treatment to verify glycosylation-dependent banding patterns

• Loading controls (e.g., beta-actin) for Western blotting

• Peptide competition assays to confirm epitope specificity

The gold standard approach uses genetic knockout controls, as demonstrated in the validation of the Sigma-Aldrich #N1660 antibody, where researchers generated NCSTN knockout HEK293 cells using CRISPR/Cas9 genome editing and confirmed the deletion through sequencing and RT-qPCR .